de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior

Class SeparateGaussianLogPrior

java.lang.Object

de.jstacs.algorithms.optimization.DifferentiableFunction

de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior

de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior

de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateGaussianLogPrior

All Implemented Interfaces:

Function, Storable, Cloneable

public class SeparateGaussianLogPrior
extends SeparateLogPrior

Class for a LogPrior that defines a Gaussian prior on the parameters of a set of DifferentiableStatisticalModels and a set of class parameters. The variances v[i] for a parameter i of a DifferentiableStatisticalModel fun[j] are determined from the base variance v[j] as
v[i] = v[j]*funs[j].getSizeOfEventSpaceForRandomVariablesOfParameter(j) .
The variances for the class parameters are used as defined by the user. The mean parameters are set to 0 for the parameters of the DifferentiableStatisticalModels and to the user-specified means for the class parameters.

Author:

Jan Grau, Jens Keilwagen

Field Summary

Fields

Modifier and Type	Field and Description
protected double[]	mus The means
protected double[]	vars2 The variances

Fields inherited from class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior

classMus, classVars, freeParameters, funs, vars

Fields inherited from class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior

UNKNOWN

Constructor Summary

Constructors

Constructor and Description
SeparateGaussianLogPrior(double[] vars, double[] classVars, double[] classMus) Creates a new SeparateGaussianLogPrior from a set of base variances vars, a set of class variances classVars and a set of class means classMus.
SeparateGaussianLogPrior(StringBuffer xml) The standard constructor for the interface Storable.

Method Summary

Modifier and Type	Method and Description
void	addGradientFor(double[] params, double[] grad) Adds the gradient of the log-prior using the current parameters to a given vector.
double	evaluateFunction(double[] x) Evaluates the function at a certain vector (in mathematical sense) x.
int	getDimensionOfScope() Returns the dimension of the scope of the Function.
String	getInstanceName() Returns a short instance name.
void	unset() Resets all internally pre-computed values, e.g.

Methods inherited from class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.SeparateLogPrior

getNewInstance, set, toXML

Methods inherited from class de.jstacs.classifiers.differentiableSequenceScoreBased.logPrior.LogPrior

evaluateGradientOfFunction

Methods inherited from class de.jstacs.algorithms.optimization.DifferentiableFunction

findOneDimensionalMin

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

vars2

protected double[] vars2

The variances

mus

protected double[] mus

The means

Constructor Detail

SeparateGaussianLogPrior

public SeparateGaussianLogPrior(double[] vars,
                                double[] classVars,
                                double[] classMus)

Creates a new SeparateGaussianLogPrior from a set of base variances vars, a set of class variances classVars and a set of class means classMus.

Parameters:

vars - the base variances for each class

classVars - the class variances

classMus - the class means

See Also:

SeparateLogPrior.SeparateLogPrior(double[], double[], double[])

SeparateGaussianLogPrior

public SeparateGaussianLogPrior(StringBuffer xml)
                         throws NonParsableException

The standard constructor for the interface Storable. Creates a new SeparateGaussianLogPrior out of its XML representation.

Parameters:

xml - the XML representation as StringBuffer

Throws:

NonParsableException - if the SeparateGaussianLogPrior could not be reconstructed out of the XML representation (the StringBuffer could not be parsed)

See Also:

SeparateLogPrior.SeparateLogPrior(StringBuffer), Storable

Method Detail

unset

public void unset()

Description copied from class: SeparateLogPrior

Resets all internally pre-computed values, e.g. the hyperparameters for each parameter.

Specified by:

unset in class SeparateLogPrior

addGradientFor

public void addGradientFor(double[] params,
                           double[] grad)

Description copied from class: LogPrior

Adds the gradient of the log-prior using the current parameters to a given vector.

Specified by:

addGradientFor in class LogPrior

Parameters:

params - the parameters

grad - the vector

evaluateFunction

public double evaluateFunction(double[] x)
                        throws DimensionException,
                               EvaluationException

Description copied from interface: Function

Evaluates the function at a certain vector (in mathematical sense) x.

Parameters:

x - the current vector

Returns:

the evaluation of the function

Throws:

DimensionException - if dim(x) != n, with

EvaluationException - if there was something wrong during the evaluation of the function

getDimensionOfScope

public int getDimensionOfScope()

Description copied from interface: Function

Returns the dimension of the scope of the Function.

Returns:

the dimension of the scope: n with

getInstanceName

public String getInstanceName()

Description copied from class: LogPrior

Returns a short instance name.

Specified by:

getInstanceName in class LogPrior

Returns:

a short instance name